MIMO Soft Demodulation via Hard-Decision Candidate Selection
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Solution Overview
Problem
MIMO systems face a tradeoff between receiver complexity and performance due to the need to recover independent information from multiple transmitter outputs, limiting their efficiency in high-capacity communications and storage systems.
Innovation Solution
A method and system that use a hard-decision demodulator to select initial candidate signal values and additional candidate values for each signal stream, followed by a soft-decision demodulator to compute a log-likelihood ratio (LLR) for digital information reconstruction in MIMO communications channels, balancing complexity and performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If full soft-decision demodulation is used to recover independent information from multiple transmitter outputs, then digital information recovery performance is improved, but receiver computational complexity increases
Solution Approach 1:
The patent segments the candidate signal values into multiple groups based on their correlation with the received signal. Instead of processing all candidate values uniformly, the system divides them into groups (e.g., first group with highest correlation, second group with next highest correlation) and processes each group separately through the soft-decision demodulator. This segmentation reduces the computational burden while maintaining recovery performance by focusing resources on the most relevant candidates.
Solution Approach 2:
The patent extracts and processes only the most relevant candidate signal values rather than all possible candidates. By selecting a subset of candidate values that have the highest correlation with the received signal and processing only those through soft-decision demodulation, the system achieves near-optimal performance with significantly reduced computational complexity compared to exhaustive processing of all candidates.
2Productivity
If MIMO systems increase dimensions to convey more information, then throughput and reliability are improved, but receiver design complexity increases
Solution Approach 1:
The patent applies segmentation to the MIMO receiver by dividing the complex task of processing multiple signal streams into manageable segments. Each signal stream's candidate values are grouped and processed separately, allowing the receiver to handle high-dimensional MIMO systems with multiple antennas and streams without being overwhelmed by computational complexity. This enables the system to maintain high throughput while managing receiver design complexity through structured processing.
Solution Approach 2:
The patent implements partial action by processing only a selected subset of candidate signal values through the computationally intensive soft-decision demodulator. Rather than exhaustively processing all possible candidate values from all MIMO streams, the system selectively processes the most promising candidates (those with highest correlation), achieving near-optimal performance with reduced computational burden that scales more gracefully with increasing MIMO dimensions.
Data Source
AI summary
Systems and methods for reconstructing digital information in a multiple-input receiver from signals transmitted by a multiple-output transmitter, in a multiple-input multiple-output (MIMO) communications channel are provided. A plurality of signal streams are obtained from a plurality of transmitted signals and a first candidate signal value is selected for each of the plurality of signal streams. A plurality of additional candidate signal values are also selected for each of the plurality of signal streams in response to selecting the first candidate signal value. A log-likelihood ratio (LLR) is computed from the plurality of signal streams based on all of the selected candidate signal values. Digital information may then be estimated based on the computed LLR.